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. Apply latest 17 May 2024. Project description and working tasks The connection between optimization and machine learning is at the heart of many recent breakthroughs in artificial intelligence and
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education to enable regions to expand quickly and sustainably. In fact, the future is made here. The Department of Computing Science is now looking for a Doctoral student in machine learning for continuous
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scientific disciplines and industry segments. The main task of the advertised position is to set up and maintain a distributed environment for collaborative projects in machine learning (ML). The work involves
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years, with a focus on creating an inclusive and bottom-up driven research environment. To further strengthen our numbers, we are now looking for a postdoctoral researcher in machine learning. Our
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at the department investigating mathematical foundations of artificial intelligence. The group covers a diverse range of topics in modern machine learning research, including geometric deep learning, non-convex
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applications poses several challenges in dealing with petabytes of data in diverse resource-constrained environments. Federated machine learning (FML) is a collaborative learning solution to handle
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or stealthy DDoS attacks is unexplored in the cloud-edge continuum. Where machine learning (ML) is deployed both for optimising performance (benign adaptation) and attack detection (DDoS), security researchers
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of injuries to the upper extremity supported by machine learning and neural networks. The position is an initiative within the framework of the research initiative "Learning and brain plasticity throughout
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their doctoral degree prior to that may also be eligible. Special reasons include absence due to illness, parental leave, appointments of trust in trade union organizations, military service, or similar
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Machine learning Candidates are expected to have good knowledge in Artificial Intelligence and good programming skills in some of the following: Python, PyTorch library, OpenAI-Gym, Prolog, ProbLog, Answer